1Faculty of Medicine, University of
Geneva, Geneva, Switzerland; 2Biomedical Imaging Group (BIG), Ecole
Polytechnique Fdrale de Lausanne (EPFL), Lausanne, Switzerland; 3Work
supported in part by the Center for Biomedical Imaging (CIBM), Geneva and Lausanne,
Switzerland

Small-animal cardiac imaging is very challenging because
we face with several problems like resolution or flux artifacts. One possible
way to assess them is the use of non-Cartesian acquisition scheme like variable
density spiral. Regridding reconstruction, which is the most popular
alternative, however introduces noticeable artifacts due to k-space
interpolation, especially when dealing with undersampled trajectories. We
propose a variational approach where the image is described by a spline model
and where an automatic adjustment of the regularizing weight is implemented. We
evaluate our framework for various degrees of the spline model and different
orders of derivation of the regularizer.